1. Field of the Invention
The present invention relates generally to 3D-2D image registration and, more particularly, to 3D-2D image registration with nine degrees of freedom (9 DoF).
2. Description of Related Art
Three-dimensional (3D) pre-operative images are ubiquitously used for surgical planning and intra-operative guidance. In surgical planning, a variety of structures, for example surgical devices, needles, prosthetics, intended incisions and anatomical structures, such as a surgical target or an adjacent structure, e.g. a critical structure, are geometrically defined in these 3D images. The intended trajectory as well as desired location and orientation of a structure are defined in a 3D coordinate system of a pre-operative image. More recent advances bring such 3D imaging capability into an operating room (OR) as well as interventional environment, for example interventional radiology (IR) or vascular and interventional radiology (VIR). A planning structure may be similarly defined in 3D intra-operative images.
An incorporation of the pre-operative 3D information into surgical intervention forms a basis for many forms of surgical guidance using a navigation system that leverages various types of rigid as well as deformable registration, for example computation of alignment between two or more coordinate systems such as reference frames of a pre-operative image, an intra-operative image and a coordinate system (“world” coordinate system) at the time of surgery.
In addition to such 3D imaging modalities, a variety of intra-operative 2D radiographic or fluoroscopic imaging systems, for example a mobile x-ray radiographic system, fixed-room x-ray radiography/fluoroscopy system; mobile C-arm for radiography/fluoroscopy or fixed-room C-arm, may be used.
An incorporation of pre-operative 3D information into intra-operatively acquired two-dimensional (2D) radiographs or fluoroscopic images can be achieved via a type of registration called 3D-2D registration (alternatively 2D-3D registration). Such methods have shown significant utility in increasing precision and accuracy of surgery and radiation therapy by bringing 3D pre-operative images and planning structures into the context of 2D images acquired during an operation. For example, in spine surgery, a 3D-2D registration method may be computed to overlay the locations of target vertebral levels that were pre-operatively identified in a 3D computed-tomography (CT) image onto intra-operative 2D radiography/fluoroscopy images [1]. Such registration and visualization may assist a surgeon in localizing the target anatomy, for example a specific vertebral level, and offer numerous advantages with regard to, for example, time, dose, cost and accuracy) in comparison to conventional methods, for example manual level counting and pre-operative fiducial screw placement, which are prone to error and may potentially result in “wrong-level” surgery.
The 3D-2D registration computes the transformation of a 3D image, for example pre-operative CT image or intra-operative CT image, such that a 2D projection image computed from the 3D image, for example a digitally reconstructed radiograph (DRR), provides a best match, in other words yields maximum similarity, to the intra-operative 2D image, for example mobile x-ray radiograph of C-arm fluoroscopy. Therefore, the 3D-2D registration effectively computes a “pose” of the DRR that best matches the true radiograph using an optimization algorithm. Conventionally, this amounts to calculation of the six degrees of freedom (DoF), i.e. the (x, y, z) position and roll, tilt, yaw, yielding the best match. Thus, for a known geometric relationship of the x-ray source and detector, the conventional 3D-2D registration methods solve for these six DoF.
These conventional 3D-2D registration methods require geometric calibration of the imaging system, i.e. the position of the x-ray source relative to the detector is determined and used as input to the registration method. Therefore, the conventional 3D-2D registration methods require that the relative position between the x-ray source and the detector is known. For example, the relative position may be measured by means of a calibration using a specially designed calibration phantom [2]. For example, in the above-mentioned 3D-2D registration method used in spine surgery 3D CT images are registered to mobile C-arm fluoroscopy in which the x-ray source and detector positions are known by means of a prior C-arm geometric calibration, and the 3D-2D registration method solves for the “pose” of the C-arm about the patient. Thus, the conventional methods can work well for a system where the x-ray source is rigidly (or almost rigidly) related to the detector.
However, the geometric calibration limits general application of the conventional 3D-2D registration methods to x-ray imaging systems involving an unconstrained source-detector geometry, for example a mobile x-ray radiography system in which the x-ray source (x-ray tube) is freely positionable above the patient in a manner that is largely unconstrained in angle and distance from the patient and detector and, thus, placement of the x-ray source with respect to the detector changes case by case.
Other imaging systems, wherein the source and detector are unconstrained in their relationship, include, for example, radiographic systems and fluoroscopic systems typical of chest radiography or under-table fluoroscopy.
Thus, a disadvantage of the conventional methods is that the geometric relationship of the x-ray source and detector must be known and fixed.